Negative-Aware Influence Maximization on Social Networks

Authors

  • Yipeng Chen Peking University
  • Hongyan Li Peking University
  • Qiang Qu Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences

DOI:

https://doi.org/10.1609/aaai.v32i1.12149

Keywords:

Influence Maximization, Social Network, Negative Users

Abstract

How to minimize the impact of negative users within the maximal set of influenced users? The Influenced Maximization (IM) is important for various applications. However, few studies consider the negative impact of some of the influenced users.We propose a negative-aware influence maximization problem by considering users' negative impact. A novel algorithm is proposed to solve the problem. Experiments on real-world datasets show the proposed algorithm can achieve 70% improvement on average in expected influence compared with rivals.

AAAI 2018 Proceedings Cover

Downloads

Published

2018-04-29

How to Cite

Chen, Y., Li, H., & Qu, Q. (2018). Negative-Aware Influence Maximization on Social Networks. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.12149

Issue

Vol. 32 No. 1 (2018): Thirty-Second AAAI Conference on Artificial Intelligence

Section

Student Abstract Track